no code implementations • 24 Jan 2024 • Chuting Yu, Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon
This paper considers Pseudo-Relevance Feedback (PRF) methods for dense retrievers in a resource constrained environment such as that of cheap cloud instances or embedded systems (e. g., smartphones and smartwatches), where memory and CPU are limited and GPUs are not present.
1 code implementation • 21 Dec 2022 • Bevan Koopman, Ahmed Mourad, Hang Li, Anton van der Vegt, Shengyao Zhuang, Simon Gibson, Yash Dang, David Lawrence, Guido Zuccon
On the basis of these needs we release an information retrieval test collection comprising real questions, a large collection of scientific documents split in passages, and ground truth relevance assessments indicating which passages are relevant to each question.
no code implementations • 12 May 2022 • Hang Li, Ahmed Mourad, Bevan Koopman, Guido Zuccon
Pseudo-Relevance Feedback (PRF) assumes that the top results retrieved by a first-stage ranker are relevant to the original query and uses them to improve the query representation for a second round of retrieval.
no code implementations • 30 Apr 2022 • Hang Li, Shuai Wang, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon
In this paper we consider the problem of combining the relevance signals from sparse and dense retrievers in the context of Pseudo Relevance Feedback (PRF).
1 code implementation • 13 Dec 2021 • Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, Guido Zuccon
Finally, we contribute a study of the generalisability of the ANCE-PRF method when dense retrievers other than ANCE are used for the first round of retrieval and for encoding the PRF signal.
1 code implementation • 8 Dec 2021 • Shuai Wang, Harrisen Scells, Ahmed Mourad, Guido Zuccon
Our results also indicate that our reproduced screening prioritisation method, (1) is generalisable across datasets of similar and different topicality compared to the original implementation, (2) that when using multiple seed studies, the effectiveness of the method increases using our techniques to enable this, (3) and that the use of multiple seed studies produces more stable rankings compared to single seed studies.
1 code implementation • 25 Aug 2021 • Hang Li, Ahmed Mourad, Shengyao Zhuang, Bevan Koopman, Guido Zuccon
Text-based PRF results show that the use of PRF had a mixed effect on deep rerankers across different datasets.